| accuracy | Average classification accuracy |
| adult | adult data set |
| advertising | advertising data set |
| bank | Bank marketing data set |
| caravan | Caravan insurance data set |
| cereal | Cereal data set |
| churn | Churn data set |
| churnCredit | Churn dataset for Credit Card Customers |
| churnTel | churnTel dataset |
| conf.mat | Confusion Matrix |
| conf.mat.plot | Plot Confusion Matrix |
| corona | Corona data set |
| fertilizer | Fertilizer data set |
| find.na | find.na |
| house | house data set |
| housePrice | housePrice dataset |
| insurance | insurance data set |
| kNN | k-Nearest Neighbour Classification |
| kNN.plot | Visualizing the Optimal Number of k |
| liver-package | liver: Foundations Toolkit and Datasets for Data Science |
| mae | Mean Absolute Error (MAE) |
| marketing | marketing data set |
| minmax | Min-Max scaling of numerical variables |
| mse | Mean Squared Error (MSE) |
| one.hot | One Hot Encoder |
| partition | Partition the data |
| prop.conf | Confdidence interval for proportion |
| redWines | Red wines data set |
| risk | Risk data set |
| scaler | Feature scaling |
| skewness | Skewness |
| skim | Skim a data frame to get useful summary statistics |
| t_conf | Confdidence interval for mean |
| whiteWines | White wines data set |
| z.conf | Confdidence interval for mean using z-distribution |
| zscore | Z-score scaling of numerical variables |
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